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DBMS > Google Cloud Datastore vs. Kinetica vs. ObjectBox vs. Teradata vs. Valentina Server

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. ObjectBox vs. Teradata vs. Valentina Server

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonObjectBox  Xexclude from comparisonTeradata  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsExtremely fast embedded database for small devices, IoT and MobileA hybrid cloud data analytics software platform (Teradata Vantage)Object-relational database and reports server
Primary database modelDocument storeRelational DBMSObject oriented DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Time Series DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitecloud.google.com/­datastorewww.kinetica.comobjectbox.iowww.teradata.comwww.valentina-db.net
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comdocs.objectbox.iodocs.teradata.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperGoogleKineticaObjectBox LimitedTeradataParadigma Software
Initial release20082012201719841999
Current release7.1, August 2021Teradata Vantage 1.0 MU2, January 20195.7.5
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache License 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C and C++
Server operating systemshostedLinuxAndroid
iOS
Linux
macOS
Windows
hosted
Linux
Linux
OS X
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononoyes
Secondary indexesyesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsnoyes infoSQL 2016 + extensionsyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Proprietary native API.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsnoyes infoUDFs, stored procedures, table functions in parallelyes
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationonline/offline synchronization between client and serverMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMnoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelyesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
Google Cloud DatastoreKineticaObjectBoxTeradataValentina Server
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More resources
Google Cloud DatastoreKineticaObjectBoxTeradataValentina Server
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